@incollection{LehnertzBialonskiHorstmannetal.2010,
  author    = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias},
  title     = {Epilepsy},
  series = {Reviews of Nonlinear Dynamics and Complexity, Volume 2},
  booktitle = {Reviews of Nonlinear Dynamics and Complexity, Volume 2},
  publisher = {Wiley-VCH},
  isbn      = {9783527628001},
  doi       = {10.1002/9783527628001.ch5},
  pages     = {159 -- 200},
  year      = {2010},
  language  = {en}
}
@article{LehnertzBialonskiHorstmannetal.2009,
  author    = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias},
  title     = {Synchronization phenomena in human epileptic brain networks},
  series = {Journal of neuroscience methods},
  volume    = {183},
  journal   = {Journal of neuroscience methods},
  number    = {1},
  issn      = {0165-0270},
  doi       = {10.1016/j.jneumeth.2009.05.015},
  pages     = {42 -- 48},
  year      = {2009},
  language  = {en}
}
@article{SchindlerBialonskiHorstmannetal.2008,
  author    = {Schindler, Kaspar A. and Bialonski, Stephan and Horstmann, Marie-Therese and Elger, Christian E. and Lehnertz, Klaus},
  title     = {Evolving functional network properties and synchronizability during human epileptic seizures},
  series = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  volume    = {18},
  journal   = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  number    = {3},
  issn      = {1089-7682},
  doi       = {10.1063/1.2966112},
  pages     = {033119},
  year      = {2008},
  language  = {en}
}
@article{HorstmannBialonskiNoenningetal.2010,
  author    = {Horstmann, Marie-Therese and Bialonski, Stephan and Noenning, Nina and Mai, Heinke and Prusseit, Jens and Wellmer, J{\"o}rg and Hinrichs, Hermann and Lehnertz, Klaus},
  title     = {State dependent properties of epileptic brain networks: Comparative graph-theoretical analyses of simultaneously recorded EEG and MEG},
  series = {Clinical Neurophysiology},
  volume    = {121},
  journal   = {Clinical Neurophysiology},
  number    = {2},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1388-2457},
  doi       = {10.1016/j.clinph.2009.10.013},
  pages     = {172 -- 185},
  year      = {2010},
  abstract  = {Objective To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval. Methods We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics. Results Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings. Conclusions Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks. Significance An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.},
  language  = {en}
}
@article{BialonskiHorstmannLehnertz2010,
  author    = {Bialonski, Stephan and Horstmann, Marie-Therese and Lehnertz, Klaus},
  title     = {From brain to earth and climate systems: Small-world interaction networks or not?},
  series = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  volume    = {20},
  journal   = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  number    = {1},
  publisher = {AIP Publishing},
  address   = {Melville, NY},
  issn      = {1089-7682},
  doi       = {10.1063/1.3360561},
  pages     = {013134},
  year      = {2010},
  abstract  = {We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.},
  language  = {en}
}